High-throughput Sample Analysis Research Articles

Development and Validation of an LC-MS/MS Method for the Determination of Plasma and Red Blood Cell Omega Fatty Acids: A Useful Diagnostic Tool

Development and Validation of an LC-MS/MS Method for the Determination of Plasma and Red Blood Cell Omega Fatty Acids: A Useful Diagnostic Tool

Exploring the Performance of Linear and Nonlinear Models of Time-of-Flight Secondary Ion Mass Spectrometry Spectra.

Multivariate statistical tools and machine learning (ML) techniques can deconvolute hyperspectral data and control the disparity between the number of samples and features in materials science. Nevertheless, the importance of generating sufficient high-quality sample replicates in training data cannot be overlooked, as it fundamentally affects the performance of ML models. Here, we present a quantitative analysis of time-of-flight secondary ion mass spectrometry (ToF-SIMS) spectra of a simple microarray system of two food dyes using partial least-squares (PLS, linear) and random forest (RF, nonlinear) algorithms. This microarray was generated by a high-throughput sample preparation and analysis workflow for fast and efficient acquisition of quality and reproducible spectra via ToF-SIMS. We drew insights from the bias-variance trade-off, investigated the performances of PLS and RF regression models as a function of training data size, and inferred the amount of data needed to construct accurate and reliable regression models. In addition, we found that the spectral concatenation of positive and negative ToF-SIMS spectra improved the model performances. This study provides an empirical basis for future design of high-throughput microarrays and multicomponent systems, for the purpose of analysis with ToF-SIMS and ML.

Combining deep learning and droplet microfluidics for rapid and label-free antimicrobial susceptibility testing of colistin

Efficient tools for rapid antibiotic susceptibility testing (AST) are crucial for appropriate use of antibiotics, especially colistin, which is now often considered a last resort therapy with extremely drug resistant Gram-negative bacteria. Here, we developed a rapid, easy and miniaturized colistin susceptibility assay based on microfluidics, which allows for culture and high-throughput analysis of bacterial samples. Specifically, a simple microfluidic platform that can easily be operated was designed to encapsulate bacteria in nanoliter droplets and perform a fast and automated bacterial growth detection in 2 h, using standardized samples. Direct bright-field imaging of compartmentalized samples proved to be a faster and more accurate detection method as compared to fluorescence-based analysis. A deep learning powered approach was implemented for the sensitive detection of the growth of several strains in droplets. The DropDeepL AST method (Droplet and Deep learning-based method for AST) developed here allowed the determination of the colistin susceptibility profiles of 21 fast-growing Enterobacterales (E. coli and K. pneumoniae), including clinical isolates with different resistance mechanisms, showing 100 % categorical agreement with the reference broth microdilution (BMD) method performed simultaneously. Direct AST of bacteria in urine samples on chip also provided accurate results in 2 h, without the need of complex sample preparation procedures. This method can easily be implemented in clinical microbiology laboratories, and has the potential to be adapted to a variety of antibiotics, especially for last-line antibiotics to optimize treatment of patients infected with multi-drug resistant strains.

Abstract 332: Improved high-throughput genomic analysis of urine samples using pixelated-ultrasound to enable personalized genomic profiling and therapeutic developments in cancer

Abstract Here we address some of the existing challenges in liquid biopsy workflows which can potentially benefit urine analysis from bladder cancer patients because approximately 1/4th of all human cancers are urological tumors. Globally, bladder cancer is the 10th most prevalent, and the 9th cause of mortality due to malignancy. The challenge addressed here is an improvement to sample preparation for sequencing. Among genders and disease states, urine samples vary in terms of cell count and hence, in DNA concentration. Therefore, it is critical to obtain consistent DNA fragments from variable samples across large cohorts of patients so that the sequencing leads to accurate identification of biomarkers of disease risk, progression, and treatment-response. In this direction, we present the advantages of a novel pixelated ultrasound technology which significantly improves sample-preparation in a very fast, economical, and high-throughput manner. Here, DNA is extracted from human urine samples and subjected to sonication to generate fragment sizes. Extracted DNA was loaded onto a regular 96-well round-bottom plate, which is sealed and placed inside the system where 12 columns of the 96-well plate are individually programmed and run simultaneously, hence enabling quick optimization. The system does not require time- and labor-intensive processing of the samples before or after the sonication which is required for other similar technology. Overall, the DNA samples were processed with significant improvement over other similar technology in terms of consistency, speed, and economy. Subsequently, the fragment sizes were analyzed. Analysis of results, as presented in the figures, show that the DNA fragment had the average size as predicted, uniform shearing, and very consistent across the 96-well plate containing different samples with no cross-contamination. The time, labour, expense, and risk turned out to be very low compared to other similar technology. The sizes were appropriate for library preparation and sequencing. The technology works consistently for both low and high cell numbers which is a critical factor for heterogenous samples from patients. In conclusion, the study presents improvements to library preparation for sequencing which fit into the larger workflow of non-invasive liquid biopsy using urine samples. The ability to obtain consistent DNA fragments in a quick and economical manner will greatly enable unique fingerprinting of an individual's cancer or cancer risk across large cohorts, with the potential for integration in automation workflows. Citation Format: Martha Evans-Holm, Nicolai Lumbres, Rwik Sen, Patricia Montilla-Perez, Marc A. Paradise, Peter Lentz. Improved high-throughput genomic analysis of urine samples using pixelated-ultrasound to enable personalized genomic profiling and therapeutic developments in cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 332.

Surface charge-induced electrospray for high-throughput analysis of complex samples and electrochemical reaction intermediates using mass spectrometry.

Electrospray-related ion sources are promising for direct mass spectrometric analysis of complex samples, but current protocols suffer from complicated components and low analytical sensitivity. Here, we propose a surface charge-induced electrospray ionization (SCIESI) inspired by flashover on an insulator surface under high voltage. This protocol not only effectively avoids contact between the sample solution and metal electrode, but also allows completion of the entire analytical process in less than 40 seconds and limits of detection in the pictogram per milliliter range. SCIESI coupled to mass spectrometry can also be used to monitor electro-chemical processes, and a number of oxidation and reduction reactions have been studied, demonstrating that it is a powerful tool for understanding electrochemical reaction mechanisms.

High-throughput N-glycoproteomics with fast liquid chromatographic separation

N-glycosylation is a common protein post translation modification, which has tremendous structure diversity and wide yet delicate regulation of protein structures and functions. Mass spectrometry-based N-glycoproteomics has become a state-of-the-art pipeline for both qualitative and quantitative characterization of N-glycosylation at the intact N-glycopeptide level, providing comprehensive information of peptide backbones, N-glycosites, monosaccharide compositions, sequence and linkage structures. For high-throughput analysis of large-cohort clinic samples, fast and high-performance separation is indispensable. Here we report our development of 1-h liquid chromatography gradient N-glycoproteomics method and accordingly optimized MS parameters. In the benchmark analysis of cancer and paracancerous tissue of hepatocellular carcinoma, 5,218 intact N-glycopeptides were identified, where 422 site- and structure-specific differential N-glycosylation on 145 N-glycoproteins was observed. The method, representing substantial increase of throughput, can be adopted for fast and efficient analysis of N-glycoproteomes at large scale.

Aptamer functionalized fluorescent probe for detection of thrombin in human serum via static quenching

Thrombin plays a pivotal role in blood coagulation, wound healing, and tumor metastasis. In this study, we developed a fluorescent probe (Apt15@QDs) by functionalizing quantum dots (QDs) with an aptamer 15 to specifically recognize thrombin. The aptamer Apt15 binds specifically to thrombin by adopting a G-quadruplex conformation, resulting in the formation of a binary complex that quenches the fluorescence of the probe. Analysis using the classical fluorescence quenching equations Stem-Volmer and Lineweaver-Burk revealed that the mechanism of quenching is static in nature. The established method was successfully applied for detecting thrombin in human serum samples. As shown from the results, the established method exhibited high sensitivity, with a limit of detection (LOD) of 8 nM, and possessed a wide linear range within the concentration span of 20 to 200 nM. Additionally, this method circumvented the need for intricate experimental procedures. Furthermore, it offered a short analysis time, obviated the requirement for additional reagents, and proved suitable for high-throughput analysis of biological samples. This study presents a sensitive, straightforward, and rapid approach for detecting thrombin in complex biological matrices.

Mass-Activated Droplet Sorting for the Selection of Lysine-Producing Escherichia coli.

Synthetic biology relies on engineering cells to have desirable properties, such as the production of select chemicals. A bottleneck in engineering methods is often the need to screen and sort variant libraries for potential activity. Droplet microfluidics is a method for high-throughput sample preparation and analysis which has the potential to improve the engineering of cells, but a limitation has been the reliance on fluorescent analysis. Here, we show the ability to select cell variants grown in 20 nL droplets at 0.5 samples/s using mass-activated droplet sorting (MADS), a method for selecting droplets based on the signal intensity measured by electrospray ionization mass spectrometry (ESI-MS). Escherichia coli variants producing lysine were used to evaluate the applicability of MADS for synthetic biology. E. coli were shown to be effectively grown in droplets, and the lysine produced by these cells was detectable using ESI-MS. Sorting of lysine-producing cells based on the MS signal was shown, yielding 96-98% purity for high-producing variants in the selected pool. Using this technique, cells were recovered after screening, enabling downstream validation via phenotyping. The presented method is translatable to whole-cell engineering for biocatalyst production.

Rapid Electrochemical Flow Analysis of Urinary Creatinine on Paper: Unleashing the Potential of Two-Electrode Detection.

The development of low-cost, disposable electrochemical sensors is an essential step in moving traditionally inaccessible quantitative diagnostic assays toward the point of need. However, a major remaining limitation of current technologies is the reliance on standardized reference electrode materials. Integrating these reference electrodes considerably restricts the choice of the electrode substrate and drastically increases the fabrication costs. Herein, we demonstrate that adoption of two-electrode detection systems can circumvent these limitations and allow for the development of low-cost, paper-based devices. We showcase the power of this approach by developing a continuous flow assay for urinary creatinine enabled by an embedded graphenic two-electrode detector. The detection system not only simplifies sensor fabrication and readout hardware but also provides a robust sensing performance with high detection efficiencies. In addition to enabling high-throughput analysis of clinical urine samples, our two-electrode sensors provide unprecedented insights into the fundamental mechanism of the ferricyanide-mediated creatinine reaction. Finally, we developed a simplified circuitry to drive the detector. This forms the basis of a smart reader that guides the user through the measurement process. This study showcases the potential of affordable capillary-driven cartridges for clinical analysis within primary care settings.

Determining superoxide dismutase content and catalase activity in mammalian cell lines

Traditional methods for determining superoxide dismutase (SOD) content and catalase (CAT) activity rely on measuring the absorbance of individual tissue (biological) samples using a cuvette and spectrophotometer, rather than cell cultures. Although there are kits available for SOD and CAT assays, these allow for high-throughput analysis of samples and might be too expensive for research laboratories in countries from the Global South, such as South Africa. This paper describes a simple and cost-effective method to determine SOD content and CAT activity in mammalian cell cultures following exposure to environmental chemical mixtures by measuring absorbance in 96-well microplates. Moreover, the equipment used for this method is considered standard for cell culture laboratories, while the reagents and consumables are easily obtainable.•Antioxidant enzyme levels can be measured in vitro in cell cultures.•The supernatant obtained can be used to determine protein concentration, SOD content, and CAT activity.•This method is simple and affordable, allowing for the analysis of multiple samples (up to 32 samples per microplate).

Understanding Molecular Transfer between Aqueous Phase and Reverse Micelles and Its Application to Bioassays in Microfluidics

Abstract Micrometer-sized water-in-oil droplets (microdroplets) are attracting attention as carriers for the high-throughput parallel analysis of trace samples. By confining trace amounts of water-soluble samples or reagents within a microdroplet, reactions and detection can be performed while suppressing diffusion dilution. Although many manipulation methods for droplets, such as mixing, merging, and splitting using microfluidic channels have been reported, concentration enrichment and purification techniques for microdroplet inclusions have been limited. Our recently developed method for selective concentration enrichment of microdroplet contents focuses on molecular transport between microdroplets and reverse micelles.

An automated spray-capillary platform for the microsampling and CE-MS analysis of picoliter- and nanoliter-volume samples.

Capillary electrophoresis mass spectrometry (CE-MS) is an emerging analytical tool for microscale biological sample analysis that offers high separation resolution, low detection limit, and low sample consumption. We recently developed a novel microsampling device, "spray-capillary," for quantitative low-volume sample extraction (as low as 15 pL/s) and online CE-MS analysis. This platform can efficiently analyze picoliter samples (e.g., single cells) with minimal sample loss and no additional offline sample-handling steps. However, our original spray-capillary-based experiments required manual manipulation of the sample inlet for sample collection and separation, which is time consuming and requires proficiency in device handling. To optimize the performance of spray-capillary CE-MS analysis, we developed an automated platform for robust, high-throughput analysis of picoliter samples using a commercially available CE autosampler. Our results demonstrated high reproducibility among 50 continuous runs using the standard peptide angiotensin II (Ang II), with an RSD of 14.70% and 0.62% with respect to intensity and elution time, respectively. We also analyzed Ang II using varying injection times to evaluate the capability of the spray-capillary to perform quantitative sampling and found high linearity for peptide intensity with respect to injection time (R2 > 0.99). These results demonstrate the capability of the spray-capillary sampling platform for high-throughput quantitative analysis of low-volume, low-complexity samples using pressure elution (e.g., direct injection). To further evaluate and optimize the automated spray-capillary platform to analyze complex biological samples, we performed online CE-MS analysis on Escherichia coli lysate digest spiked with Ang II using varying injection times. We maintained high linearity of intensity with respect to injection time for Ang II and E. coli peptides (R2 > 0.97 in all cases). Furthermore, we observed good CE separation and high reproducibility between automated runs. Overall, we demonstrated that the automated spray-capillary CE-MS platform can efficiently and reproducibly sample picoliter and nanoliter biological samples for high-throughput proteomics analysis.

Comparison of four DNA extraction methods for 16s rRNA microbiota profiling of human faecal samples

ObjectiveGrowth in large population-based studies assessing contributions of the gut microbiota to health and disease requires high-throughput sample processing and analysis methods. This study assessed the impact that modifications to a commercially available magnetic bead based, semi-automated DNA extraction kit had on determination of microbial composition, relative to an established in-house method involving a combination of mechanical and chemical lysis. DNA was extracted from faecal samples from healthy adults (n = 12; 34–69 years), microbial composition was determined by V3-V4 16s rRNA sequencing and compared between extraction methods.ResultsDiversity metrics did not differ between extraction methods. Differences in the relative abundance of key phyla, including a significantly lower abundance of the Firmicutes (p = 0.004) and higher relative abundance of the Bacteroidetes (p = 0.005) and Proteobacteria (p = 0.008) phyla were noted where the DNA extraction did not include additional chemical and mechanical lysis. Principal coordinate analysis of family and genera level data also suggested a potential for sample pre-processing to impact microbial composition. Observations of the potential for skewed microbial composition profiles from samples prepared using a semi-automated DNA extraction kit without additional sample pre-processing highlights a need for consideration of standardisation of methodological approaches to increase the comparability of microbial compositional data.

Serum proteomic analysis of peripartum cardiomyopathy reveals a unique disease with distinctive dysregulation of inflammatory and cholesterol metabolism pathways

Abstract Background: The pathophysiology of peripartum cardiomyopathy (PPCM) and its defining features when compared to other forms of cardiomyopathy remain unclear, thus limiting the development of targeted therapies. Methods: To address this knowledge gap, we utilized a systems biology approach and performed high-throughput aptamer-based proteomic analysis (SOMAscan 7K) of serum samples from women with PPCM (n = 67) or non-peripartum cardiomyopathy (NPCM, n = 31), and age-matched peripartum and non-peripartum healthy women (n = 10 each). Samples were obtained from the Investigation in Pregnancy-Associated Cardiomyopathy and the Intervention in Myocarditis and Acute Cardiomyopathy studies. Comparative analyses were performed based on the presence of cardiomyopathy and peripartum status. Results: Principal component analysis revealed distinct proteomic signatures of PPCM, NPCM, and each healthy control group (p<0.00001 for all pairwise comparisons). Comparative analyses of PPCM and NPCM identified hundreds of differentially expressed serum proteins before and after normalization to healthy controls. Pathway enrichment analyses of proteins differentially expressed in PPCM highlighted dysregulation of several biological pathways related to inflammation and cholesterol metabolism, including upregulation of the anti-inflammatory liver-X receptor/retinoid X receptor (LXR/RXR) pathway. Conclusions: Serum proteomic profiling of PPCM indicates that PPCM is a unique disease entity characterized by the dysregulation of pro-inflammatory and cholesterol metabolism-related anti-inflammatory pathways. These pathways may represent potential novel therapeutic targets in PPCM.

Towards Automated and High-Throughput Quantitative Sizing and Isotopic Analysis of Nanoparticles via Single Particle-ICP-TOF-MS.

The work described herein assesses the ability to characterize gold nanoparticles (Au NPs) of 50 and 100 nm, as well as 60 nm silver shelled gold core nanospheres (Au/Ag NPs), for their mass, respective size, and isotopic composition in an automated and unattended fashion. Here, an innovative autosampler was employed to mix and transport the blanks, standards, and samples into a high-efficiency single particle (SP) introduction system for subsequent analysis by inductively coupled plasma-time of flight-mass spectrometry (ICP-TOF-MS). Optimized NP transport efficiency into the ICP-TOF-MS was determined to be >80%. This combination, SP-ICP-TOF-MS, allowed for high-throughput sample analysis. Specifically, 50 total samples (including blanks/standards) were analyzed over 8 h, to provide an accurate characterization of the NPs. This methodology was implemented over the course of 5 days to assess its long-term reproducibility. Impressively, the in-run and day-to-day variation of sample transport is assessed to be 3.54 and 9.52% relative standard deviation (%RSD), respectively. The determination of Au NP size and concentration was of <5% relative difference from the certified values over these time periods. Isotopic characterization of the 107Ag/109Ag particles (n = 132,630) over the course of the measurements was determined to be 1.0788 ± 0.0030 with high accuracy (0.23% relative difference) when compared to the multi-collector-ICP-MS determination.

High-Throughput Ultra Performance Liquid Chromatography-Tandem Mass Spectrometry Method Validation for the Estimation of Atorvastatin and Active Metabolites in Human Plasma

A highly selective, sensitive, rugged, and rapid ultra high-performance liquid chromatography-tandem mass spectrometry method (UPLC-MS/MS) is optimized and validated for reliable quantification of atorvastatin (ATR) and its active metabolites, 2-hydroxy atorvastatin (2-ATR) and 4-hydroxy atorvastatin (4-ATR) in human plasma using atorvastatin-D5 (ATR-D5), 2-hydroxy atorvastatin-D5 (2-ATR-D5), and 4-hydroxy atorvastatin-D5 (4-ATR-D5) as deuterium-labeled internal standards (ISTDs), respectively. Isocratic mode chromatographic separation was used with a reverse-phase C18 Symmetry Shield (150 × 4.6 mm, 5.0 μm) column and a mobile phase of acetonitrile:2 mM ammonium formate (pH-3.0) [65:35%v/v] at a flow rate of 0.7 mL/min. Electrospray ionization technique with positive ion mode polarity was applied to achieve the best signal intensity and stable response. Solid-phase extraction by direct elution method was applied to extract the drugs from the plasma sample. The calibration curve range was validated from a concentration range of 0.500-250 ng/mL for ATR and 2-ATR and 0.200-20 ng/mL for 4-ATR. The within-batch and between-batch precision and accuracy were found to be consistent and reproducible for all the analytes across the validation. Extraction recoveries were >80% for all analytes and ISTDs. All peaks of analytes and the respective ISTDs were eluted within 5.2 min. In this validated method, selective multivariate analytical approaches were utilized such as best fit linearity range for different strength formulations, preventive measures for in vivo and ex vivo autodegradation of metabolites, and shorter analysis time. This validated method can be useful for challenging quantification of ATR and its active metabolites for therapeutic drug monitoring and in high-throughput clinical study sample analysis.

Depth and contaminant-shaped bacterial community structure and assembly at an aged chlorinated aliphatic hydrocarbon-contaminated site

Chlorinated aliphatic hydrocarbons (CAHs) are potentially toxic substances that have been detected in various contaminated environments. Biological elimination is the main technique of detoxifying CAHs in the contaminated sites, but the soil bacterial community at CAH-contaminated sites have been little investigated. Here, high-throughput sequencing analysis of soil samples from different depths (to 6 m depth) at an aged CAH-contaminated site has been conducted to investigate the community composition, function, and assembly of soil bacteria. The alpha diversity of the bacterial community significantly increased with increasing depth and bacterial community also became more convergent with increasing depth. Organohalide-respiring bacteria (OHRB) is considered keystone taxa to reduce the environmental stress of CAHs by reductive dechlorinate CAHs into nontoxic products, increases the alpha diversity of bacterial community and improves the stability of bacterial co-occurrence network. The high concentration of CAHs in deep soil and the stable anaerobic environment make deterministic processes dominate bacterial community assembly, while the topsoil is dominated by dispersal limitation. In general, CAHs at contaminated sites have a great impact on bacterial community, but the CAHs metabolic community acclimated in deep soil can reduce the environmental stress of CAHs, which provides foundation for the monitored natural attenuation technology in CAHs-contaminated sites.

Molecularly Imprinted Plasmonic-Based Sensors for Environmental Contaminants—Current State and Future Perspectives

The increase of production and consumption persistently introduce different pollutants into the environment. The constant development and improvement of analytical methods for tracking environmental contaminants are essential. The demand for high sample throughput analysis has hit the spotlight for developing selective sensors to avoid time-consuming sample preparation techniques. In addition, the sensor’s sensitivity should satisfy the rigorous demands of harmful compound tracking. Molecularly imprinted plasmonic-based sensors are excellent candidates to overcome selectivity and sensitivity issues. Molecularly imprinted polymers are robust, stable in aqueous and organic solvents, stable at extreme pHs and temperatures, and include a low-cost synthesis procedure. Combined with plasmonic-based techniques, they are the perspective choice for applications in the field of environmental protection. Plasmonic-based sensors offer a lower limit of detection, a broad linearity range, high sensitivity, and high selectivity compared to other detection techniques. This review outlines the optical plasmonic detection of different environmental contaminants with molecularly imprinted polymers as sensing elements. The main focus is on the environmental pollutants affecting human and animal health, such as pesticides, pharmaceuticals, hormones, microorganisms, polycyclic aromatic hydrocarbons, dyes, and metal particles. Although molecularly imprinted plasmonic-based sensors currently have their application mostly in the biomedical field, we are eager to point them out as a highly prospective solution for many environmental problems.

Metabolite Analyses Using Nuclear Magnetic Resonance (NMR) Spectroscopy in Plasma of Patients with Prostate Cancer.

Nuclear magnetic resonance (NMR) spectroscopy enables the detection and the quantification of a large range of molecules, including low-molecular-weight metabolites and lipids. NMR spectroscopy is a powerful approach when applied to the high-throughput analysis of plasma or serum samples allowing, in addition, the detection of total proteins, lipoproteins, and signals arising from the glycosylation of circulating acute-phase proteins. Here, we describe the usage of NMR spectroscopy for profiling the plasma or serum of patients with prostate cancer.

Enhanced Swine Wastewater Treatment by Constructed Wetland—Microbial Fuel Cell Systems

This paper studies the effects of planting plants and coupled microbial fuel cells (MFCs) on the decontamination capacity and purification mechanism of constructed wetlands (CWs). Four systems were set, namely CW-without plants (A1), CW-with plants (A2), CW-MFC-without plants (A3) and CW-MFC-with plants (A4). The daily reductions per unit area of chemical oxygen demand (COD) were 48.72 ± 5.42, 51.26 ± 4.10, 53.49 ± 5.44 and 58.54 ± 4.16 g·(d·m2)−1, respectively. The daily reductions per unit area of nitrogen (N) were 11.89 ± 0.73, 12.38 ± 0.76, 12.24 ± 0.79 and 13.61 ± 1.07 g·(d·m2)−1, respectively. After studying the pollutant removal efficiency, it was found that the unit area of A4 removes the highest number of pollutants, improving the area efficiency of the wetland system and fundamentally alleviating the disadvantage of the large land footprint of wetland processes. The average output voltages of A3 and A4 were 568.29 and 717.46 mV, respectively, and the maximum power densities were 4.59 and 15.87 mW/m3, respectively. In addition, after high-throughput analysis of microbial samples, anaerobic ammonia oxidising (anammox) bacteria were found to remove N from the system in the anaerobic anode region.